Biology subjects

Malphrus, K. G.

Publications and source records attributed to Malphrus, K. G..

4 recordsLinked to original sources

bioRxiv2021

Single Nuclei Transcriptome Reveals Perturbed Brain Vascular Molecules in Alzheimer's Disease

Blood-brain barrier (BBB) dysfunction is well-known in Alzheimers disease (AD), but the precise molecular changes contributing to its pathophysiology are unclear. To understand the transcriptional changes in brain vascular cells, we performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in 24 AD and control brains resulting in 79,751 nuclei, 4,604 of which formed three distinct vascular clusters characterized as activated pericytes, endothelia and resting pericytes. We identified differentially expressed genes (DEGs) and their enriched pathways in these clusters and detected the most transcriptional changes within activated pericytes. Using our data and a knowledge-based predictive algorithm, we discovered and prioritized molecular interactions between vascular and astrocyte clusters, the main cell types of the gliovascular unit (GVU) of the BBB. Vascular targets predicted to interact with astrocytic ligands have biological functions in signalling, angiogenesis, amyloid {beta} metabolism and cytoskeletal structure. Top astrocytic and vascular interacting molecules include both novel and known AD risk genes such as APOE, APP and ECE1. Our findings provide information on transcriptional changes in predicted vascular-astrocytic partners at the GVU, bringing insights to the molecular mechanisms of BBB breakdown in AD. Graphical AbstractPericytes (yellow), endothelia (salmon) and astrocytes (purple) that form the gliovascular unit (GVU) at the blood brain barrier (BBB) were interrogated for their differentially expressed genes (DEG) and vascular cell (pericyte or endothelia) to astrocyte interactions using single nucleus RNA sequencing (RNAseq) transcriptome obtained from brains of Alzheimers disease (AD) patients and controls. We identified many upregulated (red) or downregulated (blue) DEGs in AD brains in these cell types. These genes have known biological functions in amyloid {beta} (A{beta}) clearance, immune modulation, astrogliosis and neuronal death. Novel predicted interactions were identified between vascular cells and astrocytic DEGs. Collectively, our findings highlight the vast transcriptome changes that occur at the GVU and provide mechanistic insights into BBB dysfunction in AD. This figure was created with Biorender.com. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/474255v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@f48748org.highwire.dtl.DTLVardef@1ddc3f4org.highwire.dtl.DTLVardef@6bfa5eorg.highwire.dtl.DTLVardef@1024506_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2021

Transcriptional landscape of human microglia reveals robust gene expression signatures that implicates age, sex and APOE-related immunometabolic pathway perturbations

Microglia have fundamental roles in health and disease, however effects of age, sex and genetic factors on human microglia have not been fully explored. We applied bulk and single cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single cell microglia transcriptomes. We discovered microglial co-expression network modules associated with age, sex and APOE-{varepsilon}4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single cell transcriptomes revealed significant overlap between age-associated module genes and both pro-inflammatory and disease-associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2 and BIN1. Meta-analyses with published bulk and single cell microglial datasets further supported our findings. Thus, these data represent a well-characterized human microglial transcriptome resource; and highlight age, sex and APOE-related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

genetics↗

bioRxiv2021

Conserved Architecture of Brain Transcriptome Changes between Alzheimer's Disease and Progressive Supranuclear Palsy in Pathologically Affected and Unaffected Regions

We identify a striking correlation in the directionality and magnitude of gene expression changes in brain transcriptomes between Alzheimers disease (AD) and Progressive Supranuclear Palsy (PSP). Further, the transcriptome architecture in AD and PSP is highly conserved between the temporal and cerebellar cortices, indicating highly similar transcriptional changes occur in pathologically affected and "unaffected" areas of the brain. These data have broad implications for interpreting transcriptomic data in neurodegenerative disorders.

neuroscience↗

bioRxiv2020

Deciphering cellular transcriptional alterations in Alzheimer's disease brains

Large-scale brain bulk-RNAseq studies identified molecular pathways implicated in Alzheimers disease (AD), however these findings can be confounded by cellular composition changes in bulk-tissue. To identify cell intrinsic gene expression alterations of individual cell types, we designed a bioinformatics pipeline and analyzed three AD and control bulk-RNAseq datasets of temporal and dorsolateral prefrontal cortex from 685 brain samples. We detected cell-proportion changes in AD brains that are robustly replicable across the three independently assessed cohorts. We applied three different algorithms including our in-house algorithm to identify cell intrinsic differentially expressed genes in individual cell types (CI-DEGs). We assessed the performance of all algorithms by comparison to single nucleus RNAseq data. We identified consensus CI-DEGs that are common to multiple brain regions. Despite significant overlap between consensus CI-DEGs and bulk-DEGs, many CI-DEGs were absent from bulk-DEGs. Consensus CI-DEGs and their enriched GO terms include genes and pathways previously implicated in AD or neurodegeneration, as well as novel ones. We demonstrated that the detection of CI-DEGs through computational deconvolution methods is promising and highlight remaining challenges. These findings provide novel insights into cell-intrinsic transcriptional changes of individual cell types in AD and may refine discovery and modeling of molecular targets that drive this complex disease.

neuroscience↗